A Nonlinear Association Between Neighborhood Walkability and Risks of Sarcopenia in Older Adults

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A Nonlinear Association Between Neighborhood Walkability and Risks of Sarcopenia in Older Adults

https://doi.org/10.21203/rs.3.rs-65453/v1

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Background: Neighborhood walkability has been found to be positively related to physical activity and negatively associated with risks of noncommunicable diseases. However, limited studies have examined its association with sarcopenia in older adults. Thus, this study aimed to examine the association between neighborhood walk score and risks of sarcopenia in a sample of older Taiwanese adults.

Methods: A nationwide telephone-based survey targeting older adults (≥ 65 years) was conducted in Taiwan. Data on neighborhood walkability (determined by walk score of residential neighborhood), sarcopenia scores (measured by SARC-F), and personal characteristics were obtained. The relationships between walk score and risks of sarcopenia were examined using generalized additive models.

Results: A total of 1,056 older adults participated in the survey. In model 1 (sex and age) and model 2 (full-adjusted model), a nonlinear association between neighborhood walk score and risks of sarcopenia was observed. Results showed that risks of sarcopenia appear to be lower in neighborhoods with a 40-walk score (Car-Dependent; most errands require a car) and an 80-walk score (Very Walkable) and highest in the neighborhood with a 60-walk score (Somewhat Walkable).

Conclusions: The study revealed a nonlinear relationship between neighborhood walkability and risks of sarcopenia in older adults in Asian context. Results provided information to urban designers and public health practitioners that more walkable neighborhood may not necessarily protect older adults from risks of sarcopenia.

Geriatrics & Gerontology

walk score

geriatric syndrome

disease prevention

Sarcopenia is a prevalent condition in older populations characterized by age-related loss of muscle mass and function, leading to a number of negative health impacts [1]. Evidence shows that sarcopenia is related to higher risks of functional decline, disability, falls, incidence of hospitalizations, and mortality [2]. Moreover, patients with sarcopenia are reported to have higher healthcare costs than those without sarcopenia, and this contributes to greater economic burden to the healthcare systems in society [3]. It is estimated that in older community-dwelling Taiwanese, the prevalence of sarcopenia and severe sarcopenia is 7.1% and 5.6%, respectively [4]. Another study using Sluggishness, Assistance in walking, Rise from a chair, Climb stairs, Falls (SARC-F) questionnaire (a 5-item screening tool for sarcopenia) to assess sarcopenia showed that the prevalence of sarcopenia was 6.1% in older adults [5]. With the rapid increase of older population in Asia [6], there is a need to further identify the factors associated with sarcopenia to develop strategies to prevent or delay the condition in older adults.

From the socio-ecological models, a person’s health condition can be viewed as an interaction between an individual’s behavior and his/her surrounding environment [7]. Among the different dimensions of environment, the built environment (a human-constructed physical aspects) plays an important role on public’s health [8]. Notably, neighborhood-built environment, where people live their everyday lives, is considered as a foundation of health and well-being [9, 10]. This environment is particularly critical to older population because older adults may face functional decline and narrowed social networks, as they tend to spend more time in their own neighborhoods [10]. In this context, it is critical how a neighborhood-built environment can provide opportunities such as infrastructure, shops, destinations, and transportation (known as walkability) for older adults to be physically active [11] and have healthy dietary behavior [12]. Therefore, it is possible that walkable environments with favorable destinations can play a protective role to older adults’ risks of sarcopenia because a high-walkable neighborhood environment can provide more opportunities for older adults to access healthy food and engage in active daily lifestyle.

A growing body of research states that there is a connection between neighborhood walkability and older adults’ geriatric syndrome such as weight status [13–15], cognition [16], depression [17], physical function [18], and functional disability [19]. However, it remains unclear how neighborhood walkability may relate to risks of sarcopenia in older adult population. To inform the policy of Healthy Aging or Aging in Place, there is an urgent need to further provide evidence-based information on the relationship between neighborhood walkability and risks of sarcopenia. A review reports that neighborhood walkability (determined by walk score) is positively related to physical activity and negatively associated with risks of obesity, cardiovascular disease, and cancer in Western countries [20] but not associated with recommended levels of physical activity but positively related to prolonged sedentary time in Taiwan [21]. It is possible that the associations between neighborhood walkability and health outcomes may differ in different contexts. Moreover, with recent studies suggesting that there may be no linear association between neighborhood walkability and health behavior [22] or health outcomes [23], we hypothesized that there may be a nonlinear association between neighborhood walkability and risks of sarcopenia in Asian context. Thus, this study aimed to examine whether neighborhood walkability is nonlinearly associated with risks of sarcopenia in a sample of older Taiwanese adults.

Participants and procedures

This study was a cross-sectional investigation using telephone-based survey. The sampling process was to randomly digit-dial based on the national household telephone directory. The target group included older Taiwanese adults aged 65 or above. To obtain samples that correspond to typical features, our study conducted the procedure in two stages from October 2019 to January 2020. In December 2019, the total number of targeted older adults was 3,607,127. They were initially arranged into four strata according to Taiwan’s geographic areas: north, south, east, and west. Second, participants were selected based on gender (men or women) and age group (aged 65 to 74 or 75 above). After the selection process, a telephone research service company was in charge of the phone calls. Professional interviewers (with no less than 8 hours of training) used a standardized and structured questionnaire to ask participants in each phone survey after verbal informed consent. Interviews that lasted under 20 minutes (included 20 minutes) were our validated inclusion criteria. A total of 2,352 adults participated in the survey duration, and 1,068 of them finished the interview (response rate: 45.4%) with no incentives provided. Our study’s procedures were thoroughly confirmed by the Research Ethics Committee of National Taiwan Normal University (REC number: 201706HM020).

Risks of sarcopenia

To measure the risks of sarcopenia in elderly, our study used the SARC-F questionnaire to swiftly access participants’ risks for functional difficulties [24]. The SARC-F questionnaire not only had validity globally [25] but also found to associate with subsequent quality of life, hospitalization, and mortality in Taiwan [5]. The 5 selected health status of this questionnaire could reflect the consequences of sarcopenia, including sluggishness, assistance in walking, rise from a chair, climb stairs, and falls. These components were measured by asking questions how much difficulty these participants faced upon lifting things, walking around on the same floor, transferring from an armless chair or going up a flight of 10 steps, and whether they need assistance to do these movements [26]. Each question scored from 0 to 2 (0 represents no difficulty; 1, some difficulty; and 2, hard to carry out). Participants with higher score implied higher possibility of sarcopenia.

Neighborhood walkability

The Walk Score® website (Link: www.walkscore.com) was used to measure the exposure variables of neighborhood walkability. In Taiwan and Japan, the validation of Walk Score® predicting neighborhood walkability was recently acknowledged [27, 28] and had been reported to significantly correlate with geographic information system or GIS-measured walking-relevant attributes in Taiwan [28]. The 5 walkability attributes were as follows: (1) population density (r = 0.64); (2) intersection density (r = 0.70); (3) amount of local destinations (r = 0.70); (4) sidewalk availability (r = 0.38); and (5) public transportation accessibility (r = 0.53). The calculation of Walk Score® was based on the network distance from a single geographic location to 9 types of walking destinations, including malls, grocery stores, restaurants, banks, coffee shops, schools, public parks, bookstores, and entertainment venues. For raw scores calculation, each participant must provide their residential neighborhood for our researcher to input into the Walk Score® website. In generating scores, this system estimates each residential area with normalization from 0 to 100 (for adjusting intersection density and block length) [29]. Validity correction is then performed by another researcher.

Covariates

Collection of covariates was based on self-reported demographics using standardized questionnaire, including gender, age (aged 65 to 74 or above 75), education (university or higher, high or middle school, elementary or under), geographic areas (northern, middle, eastern, or southern), living status (living alone or with others), marital status (married or not, divorced or widowed), and working status (full-time job or not). In addition, participants’ BMI were calculated by their weight dividing it by the square of their height and classified into 4 categories according the standard of the Ministry of Health and Welfare of Taiwan [30] as obese (over 30 kg/m²), overweight (over 24 to below 30 kg/m²), normal weight (18.5 to 24 kg/m²), and underweight (below 18.5 kg/m²).

Statistical analyses

Data showed nonlinear associations between Walk Score® and SARC-F score. Based on the Akaike information criterion (AIC) [31], we compared the quadratic regression model and generalized additive model (GAM). Generally, the GAM showed a lower AIC value, indicating a better model fit (Appendix Table 1). There was a smooth function of the exposure variable that allowed flexible fits with relaxed assumptions on the nonlinear associations in the GAM [32]. This model provides the potential for better fits to data than purely parametric models do. The package mgcv was applied to implement the GAM in the free software R. All analyses were executed by the software R package version 3.5.0.

Table 1

Characteristics of the study sample and its unadjusted associations with SARC-F Score(n = 1,056)
Studied characteristics	N (%)
Gender
Male	500 (47.3%)
Female	556 (52.7%)
Age – mean (SD)	72.2 (5.7)
Age (years)
65–74	720 (68.2%)
75+	336 (31.8%)
Education
High school or below	790 (74.8%)
University or higher	266 (25.2%)
Living status
Alone	98 (9.3%)
Not alone	958 (90.7%)
Marital status
Married	819 (77.6%)
Unmarried/divorced/widowed	237 (22.4%)
Working status
Full-time	125 (11.8%)
Not full-time	931 (88.2%)
Body mass index
Underweight (< 18.5 kg/m²)	37 (3.5%)
Normal weight (18.5–24 kg/m²)	522 (49.4%)
Overweight (> 24 kg/m²)	497 (47.1%)
Smoking habit
Yes	77 (7.3%)
No	979 (92.7%)
Drinking habit
Yes	106 (10.0%)
No	950 (89.4%)
Food selection
Balanced	830 (78.6%)
Unbalanced	226 (21.4%)
Physical activity
Sufficient	888 (84.1%)
Insufficient	168 (15.9%)
Sitting time
Low (< 9 hours/day)	997 (94.4%)
High (≥ 9 hours/day)	59 (5.6%)

Basic characteristics of participants

A total of 1,056 older adults (men: 47.3%; mean age: 72.2 ± 5.7 years) who provided complete study variables were included in this study. Most participants had no tertiary education (74.8%), were married (77.6%), not living alone (90.7%), and with normal weight (49.9%). In addition, most of them reported no smoking (92.7%) and drinking (89.4%) habits, had balanced food selection (78.6%), engaged in sufficient levels of physical activity (84.1%), and had lower sitting time (94.4%) (Table 1). Chi-square tests showed that there were significantly proportional differences in all sociodemographic and lifestyle factors between at-risk and not at-risk sarcopenia subgroups (Table 2).

Table 2

Characteristics of the study sample (n = 1,056).
Studied characteristics	Sarcopenia				p-value
Studied characteristics	Low risk		High risk		p-value
Sex					< 0.001**
Male	479	49.0%	21	26.9%
Female	499	51.0%	57	73.1%
Age group (years)					< 0.001**
65–74	682	69.7%	38	48.7%
75+	296	30.3%	40	51.3%
Education					0.027*
high school or below	723	73.9%	67	85.9%
University or higher	255	26.1%	11	14.1%
Living status					0.033*
Alone	85	8.7%	13	16.7%
Not alone	893	91.3%	65	83.3%
Marital status					< 0.001**
Married	771	78.9%	48	61.5%
Unmarried/divorced/widowed	207	21.1%	30	38.5%
Working status					0.005**
Full-time	124	12.7%	1	1.3%
Not full-time	854	87.3%	77	98.7%
Body mass index					0.151
Underweight (< 18.5 kg/m²)	32	3.3%	5	6.4%
Normal weight (18.5–24 kg/m²)	490	50.1%	32	41.0%
Overweight (> 24 kg/m²)	456	46.6%	41	52.6%
Smoking habit					0.058
Yes	76	7.8%	1	1.3%
No	902	92.2%	77	98.7%
Drinking habit					0.007*
Yes	105	10.7%	1	1.3%
No	873	89.3%	77	98.7%
Food selection					0.001*
Balanced	780	79.8%	50	64.1%
Unbalanced	198	20.2%	28	35.9%
Physical activity					< 0.001**
Sufficient	849	86.8%	39	50.0%
Insufficient	129	13.2%	39	50.0%
Sitting time					0.002*
Low (< 7 hours/day)	144	14.7%	22	28.2%
High (≥ 7 hours/day)	834	85.3%	56	71.8%
*p < 0.05
**p < 0.001
* p value < 0.05
Model 1 adjusts for sex and age.
Model 2 adjusts for sex, age, marital status, living status, working status, education label, drinking habits, food selection, meet PA recommendation or not and prolonged sitting time.
Appendix Table 1. Results of the Akaike information criterion (AIC) value for quadratic regression and generalized additive models.
	Quadratic regression model	Generalized additive model
Walk Score	3897.295	3890.737

Walk score and risks of sarcopenia in older adults

Figure 1 shows that in model 1 (adjusting for sex and age), a nonlinear association between neighborhood walk score and risks of sarcopenia was observed. Results showed that risks of sarcopenia tend to be lower in neighborhoods with a 40-walk score (Car-Dependent; most errands require a car) and 80-walk score (Very Walkable) and highest in neighborhood with a 60-walk score (Somewhat Walkable). Furthermore, after adjusting for marital status, living status, working status, education level, drinking habits, food selection, physical activity, and sitting time (model 2), similar result was still observed.

This nationwide and representative study examined the association between neighborhood walkability and risks of sarcopenia among older adults in Asian context. To the best our knowledge, this study is the first to reveal that there is a nonlinear relationship between neighborhood walkability and older adults’ risks of sarcopenia. This novel finding may have critical implications to urban planners and public health practitioners that high-walkable neighborhoods may not necessarily prevent sarcopenia in older adults.

Several evidences show that older adults who lived in more walkable neighborhoods engaged in higher levels of physical activity [33] and had lower risks of chronic diseases [34–36]. It is possible that high-walkable environments can provide more opportunities for older adults to access healthy food and engage in active daily lifestyle and thus protect them from risks of sarcopenia. However, in our analyses, we observed a nonlinear association between neighborhood walk score and risks of sarcopenia. The environmental mechanisms that link neighborhood walkability with sarcopenia remain unclear. It could be explained by the cultural and environmental differences between Western and Asian countries. For example, a previous study examining walk score and health behaviors in older Taiwanese adults found that higher walk score category is not associated with physical activity but positively associated with prolonged sedentary time [21]. It is possible that highly walkable neighborhood environments (i.e., walker’s paradise) in Taiwan are usually crowded and accompanied by more traffic (i.e., motorcycles) [37], and older adults may tend to not go outdoors and spend more time watching TV at home instead. A Hong Kong study also found a nonlinear association between neighborhood walkability and walking behavior [38]. Another Japanese study also assumed that a highly walkable environment with many shops and public transits could possibly reduce the time spent in physical activity (i.e., commuting and daily errand), and older adults have more time being sedentary [39]. These could be reasons why older adults living in 90- to 100-walk score were still associated with higher SARC-F score. Therefore, our results may have critical implications to urban designers and public health professionals that in Asian context, older adults living in more walkable neighborhood may not have lower risks of sarcopenia. Future studies using a prospective design are warranted to further examine the relationship between neighborhood walkability and risks of sarcopenia.

This study had several limitations. First, it used self-report measures of risks of sarcopenia (SARC-F) that may lead to recall bias in older adults. Moreover, we used walk score as a composite measure of walkability rather than specific objectively assessed neighborhood walkability attributes. In addition, walk score was determined by respondents’ residential neighborhoods but not their exact addresses. Despite these limitations, these self-reported measures have shown to be valid and suitable for use in nationwide epidemiological surveys [25]. Second, because of its cross-sectional design, the present study could not determine causality. Finally, this study also had a limited representative sample since the surveys were conducted through phone calls. Thus, individuals without a household telephone (approximately 10.4% in 2018) could not be reached.

Our findings highlight a nonlinear relationship between neighborhood walk score and risks of sarcopenia in older adults in Asian context. Results provide information to urban designers and public health practitioners that more walkable neighborhood may not necessarily protect older adults from risks of sarcopenia.

Ethics approval and consent to participate

All procedures used in this study were reviewed and confirmed by the Research Ethics Committee of National Taiwan Normal University (REC number: 201706HM020).

Consent for publication

Not applicable.

Availability of data and materials

The data used during the present study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare no conflicts of interest.

Funding

This study was supported by personal grants received from the Ministry of Science and Technology of Taiwan (MOST 107-2410-H-003-117-MY2 and MOST 108-2622-8-003-001-TM1). The Ministry of Science and Technology of Taiwan was not involved in the study design, data collection process, analysis, interpretation, or writing of this manuscript.

Authors' contributions

JHP and YL conceived of the study. TFL, JHP and YL developed the methodology. TFL ran the software. TFL and YL performed formal analysis. TFL, JHP, WCH, and YL performed the investigation. JHP and YL provided resources. CSC and YL prepared the original draft preparation. JHP, TFL, CSC, WCH and YL reviewed and edited the manuscript. JHP, and YL supervised the study. CSC and WCH provided project administration. JHP and YL secured funding. All authors have read and agreed to the final version of the manuscript.

Acknowledgements

Not applicable

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Appendix Table 1. Results of the Akaike information criterion (AIC) value for quadratic regression and generalized additive models.

	Quadratic regression model	Generalized additive model
Walk Score	3897.295	3890.737

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A Nonlinear Association Between Neighborhood Walkability and Risks of Sarcopenia in Older Adults

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Version 1

Abstract

Figures

Background

Methods

Participants and procedures

Risks of sarcopenia

Neighborhood walkability

Covariates

Statistical analyses

Results

Basic characteristics of participants

Walk score and risks of sarcopenia in older adults

Discussion

Conclusions

Declarations

References

Appendix

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